• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.248-256
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• 2009

In this paper, under saturated traffic condition in a single-hop wireless sensor network, we present an analytic model that evaluates the performance of asynchronous MAC protocol which uses a preamble technique. Our model considers the impact of several important factors such as sleep cycle, the backoff mechanism and the number of contending nodes. After obtaining the cumulative backoff time of a sending node and expected delay of a receiving node, an iterative algorithm is presented for calculating the performance measures such as expected energy consumption usage per packet and latency. Simulation results show that the proposed analytic model can accurately estimate the performance measures under saturated traffic conditions.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.181-192
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• 2023

Blockchain system brought innovation in the area of accounting, credit monitoring and trade secrets. Consensus algorithm that considered the central component of blockchain, significantly influences performance and security of blockchain system. In this paper we presented four consensus protocols specifically as Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS) and Practical Byzantine Fault-Tolerance (PBFT), we also reviewed different security threats that affect the performance of Consensus Protocols and precisely enlist their counter measures. Further we evaluated the performance of these Consensus Protocols in tabular form based on different parameters. At the end we discussed a comprehensive comparison of Consensus protocols in terms of Throughput, Latency and Scalability. We presume that our results can be beneficial to blockchain system and token economists, practitioners and researchers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1454-1466
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• 2016

This paper implements an estimated ranking algorithm of closeness centrality measures in large-scale workflow-supported social networks. The traditional ranking algorithms for large-scale networks have suffered from the time complexity problem. The larger the network size is, the bigger dramatically the computation time becomes. To solve the problem on calculating ranks of closeness centrality measures in a large-scale workflow-supported social network, this paper takes an estimation-driven ranking approach, in which the ranking algorithm calculates the estimated closeness centrality measures by applying the approximation method, and then pick out a candidate set of top k actors based on their ranks of the estimated closeness centrality measures. Ultimately, the exact ranking result of the candidate set is obtained by the pure closeness centrality algorithm [1] computing the exact closeness centrality measures. The ranking algorithm of the estimation-driven ranking approach especially developed for workflow-supported social networks is named as RankCCWSSN (Rank Closeness Centrality Workflow-supported Social Network) algorithm. Based upon the algorithm, we conduct the performance evaluations, and compare the outcomes with the results from the pure algorithm. Additionally we extend the algorithm so as to be applied into weighted workflow-supported social networks that are represented by weighted matrices. After all, we confirmed that the time efficiency of the estimation-driven approach with our ranking algorithm is much higher (about 50% improvement) than the traditional approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.57-62
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• 2004

We have proposed an efficient method of word separation in a handwritten legal amount on bank check based on the spatial gaps between the connected components. The previous gap measures all suffer from the inherent problem of underestimation or overestimation that causes a deterioration in separation performance. In order to alleviate such burden, we have developed a modified version of each distance measure. Also, 4 class clustering based method of integrating three different types of distance measures has been proposed to compensate effectively the errors in each measure, whereby further improvement in performance of word separation is expected. Through a series of word separation experiments, we found that the modified distance measures show a better performance with over 2 - 3% of the word separation rate than their corresponding original distance measures. In addition, the proposed combining method based on 4-class clustering achieved further improvement by effectively reducing the errors common to two of three distance measures as well as the individual errors.

• Journal of Distribution Science
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• v.10 no.8
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• pp.15-23
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• 2012

This study is an attempt to explore the nature and characteristics of strategic impact of green strategy by environmental capital, corporate reputation, and technology strengths on the firm's performance across countries. The main question addressed in this paper relates to how corporate sustainability, corporate reputation, technology strength, and capabilities influence the firm's economic performance with respect to diverse dimensions of performance measures including sustained growth through the leading firms across countries in the United States, Canada, Europe, and Asia-Pacific countries. Particularly, this study attempts to empirically explore the directions and magnitudes of the operational links between new emerging strategic core competencies (e.g., sustainability green strategy by environmental focus for more sustainable path, corporate reputation by corporate social responsibility and image enhancement, and technology strengths to develop a new product and market) and the firm's economic performance with respect to diverse dimensions of performance such as accounting (ROE and EOA) - and market-based performance (Market value and Tobin's q). Considering all possible limitations that might exist with regard to selected samples and methods, this study demonstrates that environmental sustainability, corporate reputation, technological capabilities and competencies through R&D intensity and patent are most likely to be significantly associated with most market-based performance measures, but the strategic significance of other variables such as capital intensity, leverage, and administrative cost efficiency on performance tends to be different depending on which performance measure is used across different countries with diverse economic and business contexts.

• Journal of Korean Society for Quality Management
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• v.23 no.4
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• pp.1-12
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• 1995

Sample skewness has not received much attention from researchers to design a control chart. In this paper, control charts based on two skewness measures are studied to control a manufacturing process. One skewness measure is the third central moment about mean, the other is the third L-moment which is a linear combination of order statistics. Since the exact sampling distributions of two skewness measures are unknown, empirical sampling distributions are studied using simulation. The sampling distributions are used to design control charts for skewness and performance of two skewness measures is compared.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.93-101
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• 1997

A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper proposes three object matching algorithm using robust HD measures based on M-estimation, least trimmed square (LTS), and .alpha.-trimmed mean methods, which are more efficient than the conventional HD measures. By computer simulation with synthetic and real images, the matching performance of the conventional HD smeasures and proposed' robust ones is compared.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.376-380
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• 1997

This paper describes usability evaluation techniques for the human interface of consumer electronic products. The techniques include measures for evaluating the user performance and emotion/impression on the product. Evaluation method for collecting the measures were also surveyed and summarized. Finally, this paper describes a systematic way of finding appropriate methods for collecting a specific measures.

• Journal of the Korea Society for Simulation
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• v.3 no.2
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• pp.27-36
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• 1994

In many real-world simulation studies the several measures of performance are of interest simultaneously. There exist very limited number of studies that explain and suggest the methods or procedures of inferencing the system performances at the same time. This study presents a procedure for determining the number of simulation observations required to achieve the prespecified confidence level for several measures of system performance. Mean values are selected as the measures, for instance, expected ordering cost, expected holding cost, and expected shortage cost for a given period of time in the study of inventory problems. Basically, the batch means approach is applied and extended to develop an algorithm to carry out the procedure handling more than single parameter. The efficacy of the presented method is assessed through the experiments. The empirical results based on some stochastic systems such as queues and inventory problems show that the suggested method produces as excellent result in terms of the precision of estimated means and the number of observations required.

• ETRI Journal
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• v.28 no.6
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• pp.811-814
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• 2006

In this letter, we introduce confusion-based confidence measures for detecting an impostor in speaker recognition, which does not require an alternative hypothesis. Most traditional speaker verification methods are based on a hypothesis test, and their performance depends on the robustness of an alternative hypothesis. Compared with the conventional Gaussian mixture model-universal background model (GMM-UBM) scheme, our confusion-based measures show better performance in noise-corrupted speech. The additional computational requirements for our methods are negligible when used to detect or reject impostors.